The fate of fipronil in modular estuarine mesocosms

The degradation and corresponding product manifold for the pesticide fipronil was determined in three replicate estuarine mesocosms. Aqueous fipronil concentrations rapidly decreased over the 672 h timescale of the experiment (95% removal). Loss was apparently first-order in fipronil, although there appeared to be a change in the removal mechanism after 96 h that corresponded to a dramatic slowdown in its disappearance. The reduction product of fipronil, fipronil sulfide, was not detected in the water column; however, it formed rapidly in sediments and was identified as the major product of fipronil degradation in the system (20% yield at 672 h, with respect to initial fipronil concentration). Fipronil sulfone is thought to form primarily via biological oxidation; and, although it was generated rapidly in the water column (10% yield), only trace amounts were detected in the sediment (1% yield). The direct photolysis product of fipronil, fipronil desulfinyl, was present in all samples; it formed rapidly in the water column (4% yield) and partitioned into the sediment phase (7% yield) over the course of the experiment. The mass balance on fipronil and associated products was 42% at 672 h.     

A pilot project to detect and forecast harmful algal blooms in the northern Gulf of Mexico

More timely access to data and information on the initiation, evolution and effects of harmful algal blooms can reduce adverse impacts on valued natural resources and human health. To achieve this in the northern Gulf of Mexico, a pilot project was initiated to develop a user-driven, end-to-end (measurements to applications) observing system. A key strategy of the project is to coordinate existing state, federal and academic programs at an unprecedented level of collaboration and partnership. Resource managers charged with protection of public health and aquatic resources require immediate notice of algal events and a forecast of when, where and what adverse effects will likely occur. Further, managers require integrated analyses and interpretations, rather than raw data, to make effective decisions. Consequently, a functional observing system must collect and transform diverse measurements into usable forecasts. Data needed to support development of forecasts will include such properties as sea surface temperature, winds, currents and waves; precipitation and freshwater flows with related discharges of sediment and nutrients; salinity, dissolved oxygen, and chlorophyll concentrations (in vivo fluorescence); and remotely-sensed spatial images of sea surface chlorophyll concentrations. These data will be provided via a mixture of discrete and autonomous in situ sensing with near real-time data telemetry, and remote sensing from space (SeaWiFS), aircraft (hyperspectral imagery) or land (high-frequency radar). With calibration across these platforms, the project will ultimately provide a 4-dimensional visualization of harmful algae events in a time frame suitable to resource managers.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Trihalomethanes in Drinking Water of Greater Québec Region (Canada): Occurrence, Variations and Modelling

The levels of trihalomethanes (THMs) – the main species of by-product from water chlorination – were monitored in thedistribution systems of the five major drinking water utilitiesof the greater area of Québec City in order to investigate andmodel their occurrence on a spatial and seasonal basis. Data forTHMs and other water quality and operational parametersassociated with their formation were generated through a 16 monthsampling program involving several sites representing variablewater residence times, from the plant to the system extremity.The results demonstrate that the differences in measured THMlevels between the five utilities are mainly due to the variablequality of raw waters, the type of water treatment process beingused and the type and levels of applied disinfectant. Dependingon the utility, average THM levels were from 1.3 to 2.5 timeshigher in the system extremities than in the water leaving thetreatment plant. Also, average levels of THMs measured in summerat the distribution system extremities were, depending on theutility, from 2.5 to 5 times higher than the average levelsmeasured in winter. The seasonal differences were found to besignificantly greater than those observed by others in waterutilities in the United States and Europe and are explained inlarge part by the considerable changes, over the year, in thequality and temperature of surface waters in Southern Québec. Forthe five utilities under study, multivariate regression modelswere developed in order to predict spatial and seasonalvariations of THMs. Both residual chlorine demand and temperaturewere found to be better, statistically, as predictors for THMoccurrence. The usefulness of the developed models for routineand long term water quality management, as well as for assessmentof human exposure to THMs, are also discussed.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

Induction of cytochrome P4501A and endocrine disrupting effects of school incinerator residues

The emission of the dioxin-like compounds from on-site waste incinerators of seven schools in Kyonggi Province of Korea was evaluated by determination of the cytochrome P4501A(CYP1A) catalytic activity and antiestrogenic activity using cell culturemicrobioassay. The residue samples were extracted in a Soxhlet apparatus using toluene for 20 hr. The concentrated crude extractswere fractionated with a basic alumina column. Dioxin-like compounds were then extracted. Induction of CYP1A activity in a rat(H4IIE) hepatoma cell line was used as indicator of biologicaleffect of incinerator residues and measured as 7-ethoxyresorufin-O-deethylase(EROD) activities. The EROD activities of fraction II extracts (one of the two extracts) in the H4IIE cells were from 0.044±0.002 to 4.424±0.351 ng-TEQ g^-1 (TCDD Toxicity equivalent), showing relatively high inducing capacity. Antisetrogenicity of the extracts was measured as decrease in E₂-induced cell proliferation. Most of the extracts showed antiestrogenic activity in MCF7-BUS cell.The TEQ levels of the incinerator residues and the antiestrogenicactivities were in good correlation, strongly suggesting that thepotent toxic emissions were indeed produced from the on-site school waste semi-incinerators and could cause the antiestrogenicity.     

Comparison of Two Manual Methods of Nitrogen Dioxide Determination in Ambient Air

Sodium arsenite (modified Jacobs and Hochheiser method; hereafter referred as SA), the most widely used manual monitoring method for determination of nitrogen dioxide (NO₂) in ambient air, particularly in developing countries has been evaluated and compared with US EPA recommended equivalent method of TGS-ANSA (hereafter referred as ANSA). NO₂ concentrations generated from laboratory test atmosphere were analyzed by these two methods and were compared statistically. Laboratory evaluations showed that SA method has high sensitivity to different sampling conditions, which normally vary during actual field monitoring. Hence, correction factors for absorption efficiency were estimated for SA and ANSA methods. Absorption efficiency of NO₂ in SA method was found to be much lower (64%) as against the reported value of 82% at the method recommended sampling conditions, whereas for ANSA method, it was found 1.0 as against the reported value of 0.93. After applying derived correction factors, both the methods produced almost similar concentration values of NO₂.     

Monitoring of Butter and Ghee (Clarified Butter Fat) for Pesticidal Contamination from Cotton Belt of Haryana, India

Butter (45) and ghee (55) samples were collected from rural and urban areas of cotton growing belt of Haryana and analysed for detecting the residues of organochlorine, synthetic pyrethroid and organophosphate insecticides. The estimation was carried out by using multi residue analytical technique employing GC-ECD and GC-NPD systems equipped with capillary columns. Butter samples were comparatively more contaminated (97%) than ghee (94%), showing more contamination with organochlorine insecticides from urban samples. About 11% samples of butter showed endosulfan residues above MRL value and 2% samples had residues of synthetic pyrethroids and organophosphates each above their respective MRL values. In ghee, residues of HCH & DDT both and of endosulfan exceeded the MRL values in 5 and 20% samples, respectively. Among organophosphates, only chlorpyriphos was detected with 9% samples showing its residue above MRL value. Irrespective of contamination levels, residues above the MRL values were more in ghee. More extensive study covering other agricultural regions/zones of Haryana has been suggested to know the overall scenario of contamination of milk products.     

Fly-ash-induced oxidative stress and tolerance in Prosopis juliflora L. grown on different amended substrates

Field experiments were conducted to study the impact of metal accumulation on malondialdehyde (MDA), cysteine and non-protein thiol (NPSH) contents in the plants of Prosopis juliflora grown on the fly ash (FA) amended with soil, blue green algae (BGA) biofertilizer, farm yard manure, press mud and Rhizobium inoculation. The analysis of data revealed that the level of MDA, cysteine and NPSH was higher in the roots of the plant than leaves, which was found positively correlated with metal accumulation. An increase of 361.14, 64.25 and 305.62% in MDA, cysteine and NPSH contents, respectively was observed after 45 days in the roots of the plants grown in 100% FA as compared to 100% garden soil (GS). The level of MDA, cysteine and NPSH was found less in the plants grown on various amendments of FA showing ameliorating effect on the toxicity induced due to the accumulation of metals. The decrease in MDA, cysteine and NPSH contents was higher in Rhizobium-inoculated plants as compared to uninoculated plants grown on 100% FA. The results showed a high tolerance potential of the plant, which is further increased by inoculating the plant with FA-tolerant Rhizobium showing feasibility of using P. juliflora in environmental monitoring of FA landfills.     

Factors influencing Aerosol Characteristics over Urban Environment

Atmospheric aerosols are an important contributing factor to turbidity in urban areas besides having impact on health. Aerosol characteristics show a high degree of variability in space and time as anthropogenic share of total aerosol loading is quite substantial and is essential to monitor the aerosol features over long time scales. In the present study extensive observations of columnar aerosol optical depth (AOD), total columnar ozone (TCO) and precipitable water content (PWC) have been carried over a tropical urban city of Hyderabad, India. Significant variations of AOD have been observed during course of the day with low values of AOD during morning and evening hours and high values during afternoon hours. Spectral variation of AOD exhibits high AOD at smaller wavelengths and vice versa except a slight enhancement in AOD at 500 nm. Anomalies in AOD, particulate matter and black carbon concentrations have been observed during May, 2003. Back trajectory analysis of air mass during these episodes suggested variation in air mass trajectories. Analysis of the results suggests that air trajectories from land region north of study area cause high loading of atmospheric aerosols. The results are discussed in the paper.